Black Box Testing: Techniques for Functional Testing of Software and Systems

By T. Adams. 1996

Subfields: Program Analysis & Verification

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Citations in the corpus

HateCheck: Functional Tests for Hate Speech Detection Models (2020, background): “ing, also known as black-box testing, is a testing framework from software engineering that assesses different functionalities of a given model by validating its output on sets of targeted test cases (Beizer, 1995).”
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList (2020, background): “In particular, “behavioral testing” (also known as black-box testing) is concerned with testing di ﬀ erent capabilities of a system by validating the input-output behavior, without any knowledge of the internal structure (Beizer, 1995).”
XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models (2023, methodology): “…Tests The structure of XST EST is motivated by prior work on functional testing for NLP. Functional tests evaluate the input-output behaviour of software on sets of targeted test cases (Beizer, 1995) and were first applied as a general framework for model evaluation in NLP by Ribeiro et al. (2020).”
GUI ripping: reverse engineering of graphical user interfaces for testing (2003, methodology): “A popular technique to detect defects in software is testing [3] [2] [23].”
The Art, Science, and Engineering of Fuzzing: A Survey (2018, methodology): “The term “black-box” is commonly used in software testing [164], [35] and fuzzing to denote techniques that do not see the internals of the PUT—these techniques can observe only the input/output behavior of the PUT, treating it as a black-box.”
Asking 'Why' in AI: Explainability of intelligent systems - perspectives and challenges (2018, background): “Commonly, in software engineering, opaque systems are referred to as ‘black boxes’ while transparent systems are called ‘glass boxes’ (Beizer, 1995).”
JCrasher: an automatic robustness tester for Java (2004, background): “In black box testing [1], a tester interacts with the entire application without any”
A taxonomy of model‐based testing approaches (2012, methodology): “Boundary analysis [ 31 ] and domain analysis [ 32, Chapter 7 ] are widely accepted as fault detection heuristics and can be used as coverage criteria for test generation (for comparison with random testing, see the respective seminal papers [ 33–36 ] and the summary by Gaston and Seifert [ 37 ] ).”